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Abstract

Compressed air energy storage is suitable for large-scale electrical energy storage, which is important for integrating renewable energy sources into electric power systems. A typical compressed air energy storage plant consists of compressors, expanders, caverns, and a motor/generator set. Current cavern models used for compressed air energy storage are either accurate but highly nonlinear or linear but inaccurate. The application of highly nonlinear cavern models in power system optimization problems renders them computationally challenging to solve. In this regard, an accurate bilinear cavern model for compressed air energy storage is proposed. The charging and discharging processes in a cavern are divided into several real/virtual states. The first law of thermodynamics and ideal gas law are then utilized to derive a cavern model, i.e., a model for the variation of temperature and pressure in these processes. Thereafter, the heat transfer between the air in the cavern and the cavern wall is considered and integrated into the cavern model. By subsequently eliminating several negligible terms, the cavern model reduces to a bilinear model. The accuracy of the bilinear cavern model is verified via comparison with both an accurate nonlinear model and two sets of field-measured data. The bilinear cavern model can bemore » easily linearized and is then suitable for integration into optimization problems considering compressed air energy storage. This is verified via comparatively solving a self-scheduling problem of compressed air energy storage using different cavern models.« less

@article{osti_1501585,
title = {An accurate bilinear cavern model for compressed air energy storage},
author = {Zhan, Junpeng and Ansari, Osama Aslam and Liu, Weijia and Chung, C. Y.},
abstractNote = {Compressed air energy storage is suitable for large-scale electrical energy storage, which is important for integrating renewable energy sources into electric power systems. A typical compressed air energy storage plant consists of compressors, expanders, caverns, and a motor/generator set. Current cavern models used for compressed air energy storage are either accurate but highly nonlinear or linear but inaccurate. The application of highly nonlinear cavern models in power system optimization problems renders them computationally challenging to solve. In this regard, an accurate bilinear cavern model for compressed air energy storage is proposed. The charging and discharging processes in a cavern are divided into several real/virtual states. The first law of thermodynamics and ideal gas law are then utilized to derive a cavern model, i.e., a model for the variation of temperature and pressure in these processes. Thereafter, the heat transfer between the air in the cavern and the cavern wall is considered and integrated into the cavern model. By subsequently eliminating several negligible terms, the cavern model reduces to a bilinear model. The accuracy of the bilinear cavern model is verified via comparison with both an accurate nonlinear model and two sets of field-measured data. The bilinear cavern model can be easily linearized and is then suitable for integration into optimization problems considering compressed air energy storage. This is verified via comparatively solving a self-scheduling problem of compressed air energy storage using different cavern models.},
doi = {10.1016/j.apenergy.2019.03.104},
journal = {Applied Energy},
number = ,
volume = 242,
place = {United States},
year = {2019},
month = {3}
}

Storage devices can provide several grid services, however it is challenging to quantify the value of providing several services and to optimally allocate storage resources to maximize value. We develop a co-optimized Compressed Air Energy Storage (CAES) dispatch model to characterize the value of providing operating reserves in addition to energy arbitrage in several U.S. markets. We use the model to: (1) quantify the added value of providing operating reserves in addition to energy arbitrage; (2) evaluate the dynamic nature of optimally allocating storage resources into energy and reserve markets; and (3) quantify the sensitivity of CAES net revenues tomore » several design and performance parameters. We find that conventional CAES systems could earn an additional 23 ± 10/kW-yr by providing operating reserves, and adiabatic CAES systems could earn an additional 28 ± 13/kW-yr. We find that arbitrage-only revenues are unlikely to support a CAES investment in most market locations, but the addition of reserve revenues could support a conventional CAES investment in several markets. Adiabatic CAES revenues are not likely to support an investment in most regions studied. As a result, modifying CAES design and performance parameters primarily impacts arbitrage revenues, and optimizing CAES design will be nearly independent of dispatch strategy.« less

In this paper, we examine the potential advantages of co-locating wind and energy storage to increase transmission utilization and decrease transmission costs. Co-location of wind and storage decreases transmission requirements, but also decreases the economic value of energy storage compared to locating energy storage at the load. This represents a tradeoff which we examine to estimate the transmission costs required to justify moving storage from load-sited to wind-sited in three different locations in the United States. We examined compressed air energy storage (CAES) in three “wind by wire” scenarios with a variety of transmission and CAES sizes relative to amore » given amount of wind. In the sites and years evaluated, the optimal amount of transmission ranges from 60% to 100% of the wind farm rating, with the optimal amount of CAES equal to 0–35% of the wind farm rating, depending heavily on wind resource, value of electricity in the local market, and the cost of natural gas.« less

In this work, we examine the potential advantages of co-locating wind and energy storage to increase transmission utilization and decrease transmission costs. Co-location of wind and storage decreases transmission requirements, but also decreases the economic value of energy storage compared to locating energy storage at the load. This represents a tradeoff which we examine to estimate the transmission costs required to justify moving storage from load-sited to wind-sited in three different locations in the United States. We examined compressed air energy storage (CAES) in three “wind by wire” scenarios with a variety of transmission and CAES sizes relative to amore » given amount of wind. In the sites and years evaluated, the optimal amount of transmission ranges from 60% to 100% of the wind farm rating, with the optimal amount of CAES equal to 0–35% of the wind farm rating, depending heavily on wind resource, value of electricity in the local market, and the cost of natural gas.« less

In recent times, there has been a significant increase in intermittent renewable electricity capacity additions to the generation mix. This, coupled with an aging electrical grid that is poorly equipped to handle the ensuing mismatch between generation and use, has created a strong need for flexible, advanced bulk energy storage technologies. In this paper, one such technology recently invented and demonstrated at Oak Ridge National Laboratory is introduced and characterized. Similar to compressed-air energy storage, the Ground-Level Integrated Diverse Energy Storage (GLIDES) technology is based on gas compression/expansion, however, liquid-piston compression and expansion are utilized. In common with pumped-storage hydroelectricity,more » hydraulic turbomachines (pump/turbine) are utilized for energy storage and recovery, however, pressure vessels are utilized to create artificial elevation (head) difference, allowing pressure head of several thousands of feet to be reached. Furthermore, this paper reports on the experimental performance of the first GLIDES proof-of-concept prototype, and presents formulation and results from a validated physics-based simulation model.« less

Compressed Air Energy Storage (CAES) can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. However, conventional CAES systems rely on the combustion of natural gas, require large storage volumes, and operate at high pressures, which possess inherent problems such as high costs, strict geological locations, and the production of greenhouse gas emissions. A novel and patented hybrid thermal-compressed air energy storage (HT-CAES) design is presented which allows a portion of the available energy, from the grid or renewable sources, to operate a compressor and the remainder to be converted and stored in themore » form of heat, through joule heating in a sensible thermal storage medium. The HT-CAES design incudes a turbocharger unit that provides supplementary mass flow rate alongside the air storage. The hybrid design and the addition of a turbocharger have the beneficial effect of mitigating the shortcomings of conventional CAES systems and its derivatives by eliminating combustion emissions and reducing storage volumes, operating pressures, and costs. Storage efficiency and cost are the two key factors, which upon integration with renewable energies would allow the sources to operate as independent forms of sustainable energy. The potential of the HT-CAES design is illustrated through a thermodynamic optimization study, which outlines key variables that have a major impact on the performance and economics of the storage system. The optimization analysis quantifies the required distribution of energy between thermal and compressed air energy storage, for maximum efficiency, and for minimum cost. This study provides a roundtrip energy and exergy efficiency map of the storage system and illustrates a trade off that exists between its capital cost and performance.« less